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Workshop Report: The Governance of Decision-Making Algorithms

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Reinforcement learning

Reinforcement learning (RL) is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Reinforcement learning differs from supervised learning in not needing labelled input/output pairs to be presented, and in not needing sub-optimal actions to be explicitly corrected.

Markov decision process

In mathematics, a Markov decision process (MDP) is a discrete-time stochastic control process. It provides a mathematical framework for modeling decision making in situations where outcomes are partly random and partly under the control of a decision maker. MDPs are useful for studying optimization problems solved via dynamic programming. MDPs were known at least as early as the 1950s; a core body of research on Markov decision processes resulted from Ronald Howard's 1960 book, Dynamic Programming and Markov Processes.

Online machine learning

In computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update the best predictor for future data at each step, as opposed to batch learning techniques which generate the best predictor by learning on the entire training data set at once. Online learning is a common technique used in areas of machine learning where it is computationally infeasible to train over the entire dataset, requiring the need of out-of-core algorithms.

Stability (learning theory)

Stability, also known as algorithmic stability, is a notion in computational learning theory of how a machine learning algorithm output is changed with small perturbations to its inputs. A stable learning algorithm is one for which the prediction does not change much when the training data is modified slightly. For instance, consider a machine learning algorithm that is being trained to recognize handwritten letters of the alphabet, using 1000 examples of handwritten letters and their labels ("A" to "Z") as a training set.

Governance

Governance is the process of making and enforcing decisions within an organization or society. It is the process of interactions through the laws, social norms, power (social and political) or language as structured in communication of an organized society over a social system (family, social group, formal or informal organization, a territory under a jurisdiction or across territories). It is done by the government of a state, by a market, or by a network.

Corporate governance

Corporate governance are mechanisms, processes and relations by which corporations are controlled and operated ("governed"). "Corporate governance" may be defined, described or delineated in diverse ways, depending on the writer's purpose. Writers focused on a disciplinary interest or context (such as accounting, finance, law, or management) often adopt narrow definitions that appear purpose-specific. Writers concerned with regulatory policy in relation to corporate governance practices often use broader structural descriptions.

Deep reinforcement learning

Deep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the problem of a computational agent learning to make decisions by trial and error. Deep RL incorporates deep learning into the solution, allowing agents to make decisions from unstructured input data without manual engineering of the state space. Deep RL algorithms are able to take in very large inputs (e.g.

Social inequality

Social inequality occurs when resources in a given society are distributed unevenly, typically through norms of allocation, that engender specific patterns along lines of socially defined categories of persons. It poses and creates a gender gap between individuals that limits the accessibility that women have within society. The differentiation preference of access to social goods in the society is brought about by power, religion, kinship, prestige, race, ethnicity, gender, age, sexual orientation, and class.

Social justice

Social justice is justice in terms of the distribution of wealth, opportunities, and privileges within a society. In Western and Asian cultures, the concept of social justice has often referred to the process of ensuring that individuals fulfill their societal roles and receive their due from society. In the current movements for social justice, the emphasis has been on the breaking of barriers for social mobility, the creation of safety nets, and economic justice.

Positive psychology

Positive psychology is a branch of psychology that studies the conditions that contribute to the optimal functioning of people, groups, and institutions. It studies "positive subjective experience, positive individual traits, and positive institutions... it aims to improve quality of life." It is a field of study that has grown as individuals and researchers look for common ground on better well-being. Positive psychology began as a new domain of psychology in 1998 when Martin Seligman chose it as the theme for his term as president of the American Psychological Association.